Statistics

I know that the majority of enthusiastic baseball fans still prefer to judge players based on the traditional statistics; for hitters those are batting average (BA), runs batted in (RBI), and home runs (HR), while pitchers get earned run average (ERA), wins (W), and saves (S). The thing is, these have problems. They have no real predictive capability, and sometimes they don’t give you a full and accurate picture of past performance. Here’s a quick overview of their respective problems:

BA: measures solely whether or not the at-bat resulted in a hit; does not show value of the hit/weighs all hits equally; neglects walks

RBI: product of circumstance; runner just happens to be in scoring position when the hit takes place; dependent (not independent) measure of skill

HR: these are fine

ERA: somewhat dependent on pitcher’s defense and luck; can fluctuate wildly from year to year because of this; not a good predictor of future performance (again, because of luck and defense)

W(in): a bad statistic; dependent largely on run (offensive) support by the pitcher’s own team; pitcher can give up 7 runs in 5 innings, and still get a win if his team scores 8; bullpen’s ability to hold a lead also affects Wins

S(ave): the worst statistic in baseball because it often adversely affects how managers manage the game; example: 8th inning, bases are loaded with one out, “set-up man” is in the game, his team has a 3-1 lead. Most managers will leave their “closer” (best reliever) in the bullpen, because is only supposed to pitch the 9th inning and get a Save, but the game’s outcome probably rests on this situation; this statistic measures a pitcher’s success at doing something that really isn’t that hard to do (get 3 outs before opponent scores enough runs to tie); not all saves are created equal – Pitcher A has a 5-2 lead and gives up 2 runs, but holds on for a 5-4 lead (gets a save), Pitcher B has a 1-0 lead and strikes out the side in order (gets a save)

Instead of these traditional (and largely flawed) statistics, I prefer:

OBP: on-base percentage; measurement of how often the player’s at-bat results in getting on base; an average OBP is about .340, anything approaching .400 is excellent

SLG: slugging percentage; measurement of total bases reached per at-bat; SLG’s value is relative to a player’s position; a 2B that slugs .450 is much more valuable than a 1B that slugs .450

OPS: the sum of OBP + SLG; good (but not perfect, undervalues OBP) measurement of player’s total offensive performance; value is also relative to a player’s position

OPS+: measurement of a player’s OPS against league average; league average is defined as 100 – anything below is below-average, and above is above-average; 120 OPS+ means the player hits 20% better than league average

EqA: equivalent average; created by Baseball Prospectus’s Clay Davenport, it’s a measure of a player’s total offensive value per out, adjusted for league offensive level, ballpark, team pitching and baserunning. And it’s purposefully scaled to resemble batting average for easy use; an average EqA is always .260. The supercomplicated formula is here.

VORP: value over replacement player; the number of runs a player contributes beyond what a replacement-level player at that position would contribute; does not take defense into account

WARP: wins above replacement player; same general idea as VORP, except includes fielding as well

WHIP: for pitchers; walks and hits allowed per inning pitched

K/9: for pitchers; strikeouts accumulated per nine innings of play

BB/9: for pitchers; walks allowed per nine innings of play

HR/9: for pitchers; home runs surrendered per nine innings of play

K/BB: for pitchers; the ratio of strikeouts to walks allowed; valuable statistic because it isolates things that the pitcher himself can control (his ability/inability to throw strikes)

ERA+: for pitchers; same general idea as OPS+; measurement of ERA against league average; league average is defined as 100

BABIP: batting average on balls in play; the statistic’s main function is to show the effects of defense and luck on a pitcher or hitter’s performance; for pitchers, a high BABIP means the pitcher has been abnormally unlucky (many of the batted balls have found holes in the defense and resulted in hits); for hitters, it means the opposite; for pitchers, a low BABIP means the pitcher has be abnormally lucky (few of the batted balls have resulted in hits); for hitters, it means the opposite; an average BABIP is about .290

UZR: Ultimate Zone Rating, for fielders; a good indicator of a fielder’s range; full explanation is here

LD%: line drive percentage; for hitters, the percentage of batted balls that are line drives; for pitchers, the percentage of batted balls surrendered that are line drives; useful in wading through the general randomness of batted ball randomness and in revealing the underlying performance of hitters and pitchers

GB%: ground ball percentage; for hitters and pitchers, the percentage of batted balls that result in grounders

FB%: fly ball percentage; for hitters and pitchers, the percentage of batted balls that result in fly balls

I know that’s a lot to look through, and I promise to try not to go too crazy with these statistics. But at least you now have some context for what exactly I’m talking about. Some of these stats will appear more often than others, but they all make appearances. If you’re a little bit patient, I think these stats are relatively easy to pick up after some practice.